4 papers
Designing Discontinuities
Ibtihal Ferwana, Suyoung Park, Ting-Yi Wu +1
Discontinuities can be fairly arbitrary but also cause a significant impact on outcomes in larger systems. Indeed, their arbitrariness is why they have been used to infer causal re…
Learning Optimal Features via Partial Invariance
Moulik Choraria, Ibtihal Ferwana, Ankur Mani +1
Learning models that are robust to distribution shifts is a key concern in the context of their real-life applicability. Invariant Risk Minimization (IRM) is a popular framework th…
Optimal Recovery for Causal Inference
Ibtihal Ferwana, Lav R. Varshney
Problems in causal inference can be fruitfully addressed using signal processing techniques. As an example, it is crucial to successfully quantify the causal effects of an interven…
Balancing Fairness and Robustness via Partial Invariance
Moulik Choraria, Ibtihal Ferwana, Ankur Mani +1
The Invariant Risk Minimization (IRM) framework aims to learn invariant features from a set of environments for solving the out-of-distribution (OOD) generalization problem. The un…